Cultural advice

The Australian National University acknowledges, celebrates and pays our respects to the Ngunnawal and Ngambri people of the Canberra region and to all First Nations Australians on whose traditional lands we meet and work, and whose cultures are among the oldest continuing cultures in human history.

Aboriginal and Torres Strait Islander peoples are advised that ANU Library collections may include images, names, voices, and other representations of deceased persons.

Material in the collection may contain terms, language or views that reflect the period in which the item was created and may be considered inappropriate today.

Decomposition of Differentials in Health Expectancies From Multistate Life Tables: A Research Note

dc.contributor.authorShen, Tianyu
dc.contributor.authorRiffe, Tim
dc.contributor.authorPayne, Collin
dc.contributor.authorCanudas-Romo, Vladimir
dc.date.accessioned2025-03-27T04:52:28Z
dc.date.available2025-03-27T04:52:28Z
dc.date.issued2023
dc.date.updated2023-12-17T07:16:53Z
dc.description.abstractMultistate modeling is a commonly used method to compute healthy life expectancy. However, there is currently no analytical method to decompose the components of differentials in summary measures calculated from multistate models. In this research note, we propose a derivative-based method to decompose the differentials in population-based health expectancies estimated via a multistate model into two main components: the proportion resulting from differences in initial health structure and the proportion resulting from differences in health transitions. We illustrate the method using data on activities of daily living from the U.S. Health and Retirement Study to decompose the sex differential in disability-free life expectancy (HLE) among older Americans. Our results suggest that the sex gap in HLE results primarily from differences in transition rates between disability states rather than from the initial health distribution of female and male populations. The methods introduced here will enable researchers, including those working in fields other than health, to decompose the relative contribution of initial population structure and transition probabilities to differences in state-specific life expectancies from multistate models.
dc.format.mimetypeapplication/pdfen_AU
dc.identifier.issn1533-7790
dc.identifier.urihttps://hdl.handle.net/1885/733743720
dc.language.isoen_AUen_AU
dc.provenanceThis is an open access arti cle dis trib uted under the terms of a Creative Commons license (CC BY-NC-ND 4.0).
dc.publisherSpringer
dc.relationhttp://purl.org/au-research/grants/arc/DE210100087
dc.rights©2023 The authors
dc.rights.licenseCreative Commons Attribution licence
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourceDemography
dc.subjectMultistate life table
dc.subjectDecomposition
dc.subjectDisabilityfree life expec tancy
dc.subjectFormal demography
dc.subjectHealth
dc.titleDecomposition of Differentials in Health Expectancies From Multistate Life Tables: A Research Note
dc.typeJournal article
dcterms.accessRightsOpen Access
local.bibliographicCitation.issue6
local.bibliographicCitation.lastpage1688
local.bibliographicCitation.startpageJan1675
local.contributor.affiliationShen, Tianyu, College of Arts and Social Sciences, ANU
local.contributor.affiliationRiffe, Tim, Max Planck Institute for Demographic Research
local.contributor.affiliationPayne, Collin, College of Arts and Social Sciences, ANU
local.contributor.affiliationCanudas-Romo, Vladimir, College of Arts and Social Sciences, ANU
local.contributor.authoruidShen, Tianyu, u6551511
local.contributor.authoruidPayne, Collin, u1057660
local.contributor.authoruidCanudas-Romo, Vladimir, u1019088
local.description.notesImported from ARIES
local.identifier.absfor440304 - Mortality
local.identifier.absfor440399 - Demography not elsewhere classified
local.identifier.absseo150202 - Demography
local.identifier.ariespublicationa383154xPUB45054
local.identifier.citationvolume11058373
local.identifier.doi10.1215/00703370-11058373
local.publisher.urlhttps://read.dukeupress.edu/
local.type.statusPublished Version
publicationvolume.volumeNumber60

Downloads

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
1675shen.pdf
Size:
3.3 MB
Format:
Adobe Portable Document Format